There is a fundamental gap in understanding why women awaiting heart transplantation have a higher mortality rate than men. The long-term goal of this project is to optimize timing and candidacy for advanced heart failure therapy in order to improve healthcare and reduce heart transplant waitlist mortality. The objective of this research application is to use a contemporary cohort to evaluate sex differences in heart transplant waitlist mortality and create a survival model that better predicts need for advanced heart failure therapy. The central hypothesis is that sex differences in heart failure mortality among patients awaiting transplantation are due to sex differences in prognostic risk factors. The rationale for the proposed research is that sex differences in prognostic risk factors have been identified in other heart failure cohorts and creation of risk prediction models has successfully reduced waitlist mortality for lung, liver, and kidney transplantation. The specific aims of this research proposal are: 1) to identify sex-specific risk factors for survival in heart failure patients awaitng heart transplantation and changes in risk factors over time using the national registry (Scientific Registry of Transplant Recipients, SRTR), 2) to develop a survival model for patients awaiting heart transplant using the SRTR database, and 3) to validate that the survival model improves prediction of mortality for the general population of patients awaiting transplantation. The approach is innovative because it challenges and seeks to shift current heart failure research and clinical practice paradigms by taking into account the differences between women and men to create a heart failure survival model that will lay the foundation to change a rule based hear transplant allocation system to a state of the art survival model based system. The survival model will be created with innovative machine learning statistical methods that do not require advance knowledge of interactions between variables or the parametric relation of variables (linearity or non-linearity) to patient survival. The proposed research is significant, because few studies have explored sex differences in prognostic risk factors despite known sex differences in heart failure survival. Furthermore, by creating the first heart failure survival model that includes sex specific risk factors and modern medical/device therapy with adequate representation of women and men we will be significantly advancing the heart failure field. This model, which is derived from our national transplant registry, will improe survival prediction for advanced heart failure patients and can be used to inform and enhance organ allocation policy in the United States. Clinical heart failure studies can also be designed i the future to include women with similar risk of mortality to men in order to improve treatment for both sexes. Ultimately, such knowledge has the potential to empower clinicians and researchers to provide the right therapies for the right patient at the right time.